Multi-ethnic genetic study greatly expands knowledge about regulation of glucose levels
A new analysis of six genetic data sets from people in different parts of the world has yielded a wealth of discoveries about the wide array of genes affecting control of glucose (sugar) levels in human beings. The study of more than 280,000 people, 30 percent of whom had non-European heritage and none of whom had diabetes, looked at whether genetic variations across the genome were associated with 4 different measures of glucose control or insulin levels. In this way, the researchers identified 99 more regions of the genome affecting glucose levels than had been known previously, 24 of which could not have been identified by simply enlarging the European data set to match the size of the multi-ethnic collection. Data from other studies conducted about the same time show that 27 of the 99 regions are linked to type 2 diabetes risk in East Asian and trans-ancestry studies; it remains to be determined whether the remaining 72 gene regions affect the risk of diabetes or simply contribute to normal variation in glucose levels among people without diabetes. Because these regions of the genome are large enough to contain multiple genes, the researchers sought to narrow these down to identify the most likely genes affecting glucose levels. Importantly, including genetic data from varied groups was instrumental in helping identify potential candidate genes within the genetic regions. Among the other key findings of the study, 80 percent of the glucose-level affecting genetic variations were found in most or all of the lineages, suggesting significant commonality in the genetics of blood glucose control. However, genetic risk scores for type 2 diabetes that had been previously developed based primarily on research with people of European descent proved significantly less predictive in other populations, demonstrating another key reason for studying the biology of glucose control in people with a wide array of differing ancestries, an approach that also may accelerate the search for new and better ways to treat or prevent the disease.
Chen J, Spracklen CN, Marenne G,…Barroso I for the Meta-analysis of Glucose and Insulin-related Traits Consortium. The trans-ancestral genomic architecture of glycemic traits. Nat Genet 53: 840-860, 2021.